How To Comply with the February 2025 EU AI Literacy Act

Introduction

As of February 2, 2025, the European Union's AI Act mandates that providers and deployers of AI systems ensure their staff and associated personnel possess adequate AI literacy. This requirement emphasizes that understanding AI is now a compulsory aspect of compliance within the EU. AI literacy, its relevance, compliance requirements, and how to establish an effective AI literacy program are all addressed in this article.
‍

AI Literacy: What Is It?

Organizations are required by the EU AI Act to guarantee that their stakeholders and workers possess a sufficient degree of AI literacy, considering elements like:

• Technical knowledge
• Experience
• Education and training
• The context in which AI systems are used.
• The individuals or groups affected by AI deployment.
  ‍

Who is Affected?

The AI literacy requirement applies to organizations that:

• Provide AI systems (develop and offer AI technologies)
• Deploy AI systems (integrate AI into business operations and customer interactions)
  ‍

Enkrypt AI platform helps organizations to conduct risk classification on their AI systems. As you see in Figure 1 below.

What Needs to Be Done?

Organizations must prepare an evidence document outlining their AI literacy initiatives. This document should address the following areas:
‍

1. Organizational Information

• Size: Large, Medium, or Small
• Sector: (e.g., Finance, Insurance, Healthcare, Technology, etc.)
• Role: Provider and/or Deployer of AI systems
• AI System Usage: Briefly describe how AI is used (e.g., automation, risk mitigation, efficiency enhancement, etc.)
  ‍

2. AI Literacy Approach

• Status: Fully implemented, partially implemented, or in development
• Target Group: AI developers, management, general employees, etc.
• Overview of AI Literacy Program: Training platforms, internal academies, course structures, etc.
• Consideration of Technical Knowledge & Training: Levels of training (basic, intermediate, advanced), expert involvement, and access criteria
• Contextual Adaptation: How training aligns with real-world AI applications within the organization
• Impact & Monitoring: KPIs such as number of trained employees, skill improvements, satisfaction ratings, and career growth
• Challenges & Solutions: Addressing AI skill gaps, keeping up with AI advancements, ensuring effective training
• Future Improvements: Updates to training, incorporation of new AI topics, and continuous learning mechanisms
  ‍

Case Study: AI Literacy in a Large Organization

Organization Details

• Size: Large (250+ employees)
• Sector: Insurance & Asset Management
• Role: Provider and Deployer of AI systems
• AI System Usage: AI is integrated across product design, pricing, underwriting, marketing, claims management, and internal operations
  ‍

AI Literacy Implementation

• Status: Fully implemented
• Target Group: Organization’s staff
• Overview:
  • Part of a global digital upskilling initiative since 2019
  • Two main components:
    • Global e-learning platform with categorized training sessions
    • Internal academies for specialized AI roles (Data Scientists, AI Business Translators, etc.)
      ‍

Training Structure

• Basic Training: AI fundamentals for all employees
• Intermediate Training: Technical deep dives for AI system users
• Advanced Training: Expert-led sessions for AI developers and maintainers
• Assessment-based Access: Ensures appropriate training level for employees
• Collaboration with Universities: Developing AI roles and expertise
  ‍

Contextual Adaptation & Impact

• Training incorporates sector-specific AI applications
  
• Key Performance Indicators (KPIs):
  • 5,200+ employees transitioned to STEM roles
  • 40%+ of trained employees saw role evolution
  • 18+ new AI-driven services launched
    
• Impact monitored via:
  • Training participation rates
  • Skill improvements & satisfaction ratings
  • Career advancements post-training
    ‍

Challenges & Future Improvements

• Challenges:
  • AI skill shortages addressed through internal reskilling
  • Keeping training up-to-date with AI advancements
    
• Future Enhancements:
  • Annual reviews incorporating new AI topics (e.g., generative AI)
  • Feedback-driven content updates
  • Expansion of specialized AI academies
    ‍

Why AI Literacy Matters

• Ensures compliance with the EU AI Act
• Enhances workforce adaptability to AI-driven transformations
• Builds trust and mitigates AI-related risks
• Strengthens organizational competitiveness in the AI era
  ‍

How to Get Started

• Assess AI literacy levels in your organization
• Develop a structured AI literacy program tailored to your AI usage
• Implement and monitor training initiatives with measurable KPIs
• Continuously update training content based on evolving AI trends
  ‍

Conclusion

Organizations must act now to meet the EU AI Act’s AI literacy requirements before the February 2025 deadline. Building a strong AI literacy framework will not only ensure compliance but also drive innovation and responsible AI adoption within your organization.
‍

We are extensively covering how organizations can prepare for the EU AI Act enforcement timelines. Check our previous blog How to Navigate EU AI Act. We will be sharing more about EU AI Act and how Enkrypt AI helps in making AI systems compliant.